The Structural Basis for the Interdependence of Drug Resistance in the HIV-1 Protease

The human immunodeficiency virus type 1 (HIV-1) protease (PR) is a critical drug target as it is responsible for virion maturation. Mutations within the active site (1°) of the PR directly interfere with inhibitor binding while mutations distal to the active site (2°) to restore enzymatic fitness. Increasing mutation number is not directly proportional to the severity of resistance, suggesting that resistance is not simply additive but that it is interdependent. The interdependency of both primary and secondary mutations to drive protease inhibitor (PI) resistance is grossly understudied. To structurally and dynamically characterize the direct role of secondary mutations in drug resistance, I selected a panel of single-site mutant protease crystal structures complexed with the PI darunavir (DRV). From these studies, I developed a network hypothesis that explains how mutations outside the active site are able to perpetuate changes to the active site of the protease to disrupt inhibitor binding. I then expanded the panel to include highly mutated multi-drug resistant variants. To elucidate the interdependency between primary and secondary mutations I used statistical and machine-learning techniques to determine which specific mutations underlie the perturbations of key inter-molecular interactions. From these studies, I have determined that mutations distal to the active site are able to perturb the global PR hydrogen bonding patterns, while primary and secondary mutations cooperatively perturb hydrophobic contacts between the PR and DRV. Discerning and exploiting the mechanisms that underlie drug resistance in viral targets could proactively ameliorate both current treatment and inhibitor design for HIV-1 targets

Characterizing protein-ligand binding using atomistic simulation and machine learning: Application to drug resistance in HIV-1 protease

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few closely related systems has guided our understanding of the mechanisms by which changes like ligand binding or mutation can alter function. The general problem of detecting and interpreting such mechanisms from simulations of many related systems, however, remains a challenge. This problem is addressed here by applying supervised and unsupervised machine learning techniques to a variety of thermodynamic observables extracted from molecular dynamics simulations of different systems. As an important test case, these methods are applied to understanding the evasion by HIV-1 protease of darunavir, a potent inhibitor to which resistance can develop via the simultaneous mutation of multiple amino acids. Complex mutational patterns have been observed among resistant strains, presenting a challenge to developing a mechanistic picture of resistance in the protease. In order to dissect these patterns and gain mechanistic insight on the role of specific mutations, molecular dynamics simulations were carried out on a collection of HIV-1 protease variants, chosen to include highly resistant strains and susceptible controls, in complex with darunavir. Using a machine learning approach that takes advantage of the hierarchical nature in the relationships among sequence, structure and function, an integrative analysis of these trajectories reveals key details of the resistance mechanism, including changes in protein structure, hydrogen bonding and protein-ligand contacts

Interdependence of Inhibitor Recognition in HIV-1 Protease

Molecular recognition is a highly interdependent process. Subsite couplings within the active site of proteases are most often revealed through conditional amino acid preferences in substrate recognition. However, the potential effect of these couplings on inhibition and thus inhibitor design is largely unexplored. The present study examines the interdependency of subsites in HIV-1 protease using a focused library of protease inhibitors, to aid in future inhibitor design. Previously a series of darunavir (DRV) analogs was designed to systematically probe the S1\u27 and S2\u27 subsites. Co-crystal structures of these analogs with HIV-1 protease provide the ideal opportunity to probe subsite interdependency. All-atom molecular dynamics simulations starting from these structures were performed and systematically analyzed in terms of atomic fluctuations, intermolecular interactions, and water structure. These analyses reveal that the S1\u27 subsite highly influences other subsites: the extension of the hydrophobic P1\u27 moiety results in 1) reduced van der Waals contacts in the P2\u27 subsite, 2) more variability in the hydrogen bond frequencies with catalytic residues and the flap water, and 3) changes in the occupancy of conserved water sites both proximal and distal to the active site. In addition, one of the monomers in this homodimeric enzyme has atomic fluctuations more highly correlated with DRV than the other monomer. These relationships intricately link the HIV-1 protease subsites and are critical to understanding molecular recognition and inhibitor binding. More broadly, the interdependency of subsite recognition within an active site requires consideration in the selection of chemical moieties in drug design; this strategy is in contrast to what is traditionally done with independent optimization of chemical moieties of an inhibitor

A Direct Interaction with RNA Dramatically Enhances the Catalytic Activity of the HIV-1 Protease In Vitro

The mechanisms regulating HIV-1 protease (PR) activity are poorly understood.RNA accelerates cleavage of multiple substrates, regardless of RNA-binding ability.The HIV-1 PR can interact with nucleic acid to increase its catalytic efficiency.The interaction is primarily electrostatic, but size/structural determinants exist.Interactions between the HIV-1 PR and RNA could affect PR activity in the virion.Though the steps of human immunodeficiency virus type 1 (HIV-1) virion maturation are well documented, the mechanisms regulating the proteolysis of the Gag and Gag-Pro-Pol polyproteins by the HIV-1 protease (PR) remain obscure. One proposed mechanism argues that the maturation intermediate p15NC must interact with RNA for efficient cleavage by the PR. We investigated this phenomenon and found that processing of multiple substrates by the HIV-1 PR was enhanced in the presence of RNA. The acceleration of proteolysis occurred independently from the substrate's ability to interact with nucleic acid, indicating that a direct interaction between substrate and RNA is not necessary for enhancement. Gel-shift assays demonstrated the HIV-1 PR is capable of interacting with nucleic acids, suggesting that RNA accelerates processing reactions by interacting with the PR rather than the substrate. All HIV-1 PRs examined have this ability; however, the HIV-2 PR does not interact with RNA and does not exhibit enhanced catalytic activity in the presence of RNA. No specific sequence or structure was required in the RNA for a productive interaction with the HIV-1 PR, which appears to be principally, though not exclusively, driven by electrostatic forces. For a peptide substrate, RNA increased the kinetic efficiency of the HIV-1 PR by an order of magnitude, affecting both turnover rate (kcat) and substrate affinity (Km). These results suggest that an allosteric binding site exists on the HIV-1 PR and that HIV-1 PR activity during maturation could be regulated in part by the juxtaposition of the enzyme with virion-packaged RNA

A Direct Interaction with RNA Dramatically Enhances the Catalytic Activity of the HIV-1 Protease In Vitro

Though the steps of human immunodeficiency virus type 1 (HIV-1) virion maturation are well documented, the mechanisms regulating the proteolysis of the Gag and Gag-Pro-Pol polyproteins by the HIV-1 protease (PR) remain obscure. One proposed mechanism argues that the maturation intermediate p15NC must interact with RNA for efficient cleavage by the PR. We investigated this phenomenon and found that processing of multiple substrates by the HIV-1 PR was enhanced in the presence of RNA. The acceleration of proteolysis occurred independently from the substrate\u27s ability to interact with nucleic acid, indicating that a direct interaction between substrate and RNA is not necessary for enhancement. Gel-shift assays demonstrated the HIV-1 PR is capable of interacting with nucleic acids, suggesting that RNA accelerates processing reactions by interacting with the PR rather than the substrate. All HIV-1 PRs examined have this ability; however, the HIV-2 PR does not interact with RNA and does not exhibit enhanced catalytic activity in the presence of RNA. No specific sequence or structure was required in the RNA for a productive interaction with the HIV-1 PR, which appears to be principally, though not exclusively, driven by electrostatic forces. For a peptide substrate, RNA increased the kinetic efficiency of the HIV-1 PR by an order of magnitude, affecting both turnover rate (k(cat)) and substrate affinity (K(m)). These results suggest that an allosteric binding site exists on the HIV-1 PR and that HIV-1 PR activity during maturation could be regulated in part by the juxtaposition of the enzyme with virion-packaged RNA

Elucidating the Interdependence of Drug Resistance from Combinations of Mutations

HIV-1 protease is responsible for the cleavage of 12 nonhomologous sites within the Gag and Gag-Pro-Pol polyproteins in the viral genome. Under the selective pressure of protease inhibition, the virus evolves mutations within (primary) and outside of (secondary) the active site, allowing the protease to process substrates while simultaneously countering inhibition. The primary protease mutations impede inhibitor binding directly, while the secondary mutations are considered accessory mutations that compensate for a loss in fitness. However, the role of secondary mutations in conferring drug resistance remains a largely unresolved topic. We have shown previously that mutations distal to the active site are able to perturb binding of darunavir (DRV) via the protein\u27s internal hydrogen-bonding network. In this study, we show that mutations distal to the active site, regardless of context, can play an interdependent role in drug resistance. Applying eigenvalue decomposition to collections of hydrogen bonding and van der Waals interactions from a series of molecular dynamics simulations of 15 diverse HIV-1 protease variants, we identify sites in the protease where amino acid substitutions lead to perturbations in nonbonded interactions with DRV and/or the hydrogen-bonding network of the protease itself. While primary mutations are known to drive resistance in HIV-1 protease, these findings delineate the significant contributions of accessory mutations to resistance. Identifying the variable positions in the protease that have the greatest impact on drug resistance may aid in future structure-based design of inhibitors

Drug resistance conferred by mutations outside the active site through alterations in the dynamic and structural ensemble of HIV-1 protease

HIV-1 protease inhibitors are part of the highly active antiretroviral therapy effectively used in the treatment of HIV infection and AIDS. Darunavir (DRV) is the most potent of these inhibitors, soliciting drug resistance only when a complex combination of mutations occur both inside and outside the protease active site. With few exceptions, the role of mutations outside the active site in conferring resistance remains largely elusive. Through a series of DRV-protease complex crystal structures, inhibition assays, and molecular dynamics simulations, we find that single and double site mutations outside the active site often associated with DRV resistance alter the structure and dynamic ensemble of HIV-1 protease active site. These alterations correlate with the observed inhibitor binding affinities for the mutants, and suggest a network hypothesis on how the effect of distal mutations are propagated to pivotal residues at the active site and may contribute to conferring drug resistance

Cognitive Control of Episodic Memory in Schizophrenia: Differential Role of Dorsolateral and Ventrolateral Prefrontal Cortex.

BackgroundDorsal (DLPFC) and ventral (VLPFC) subregions in lateral prefrontal cortex play distinct roles in episodic memory, and both are implicated in schizophrenia. We test the hypothesis that schizophrenia differentially impairs DLPFC versus VLPFC control of episodic encoding.MethodsCognitive control was manipulated by requiring participants to encode targets and avoid encoding non-targets based upon stimulus properties of test stimuli. The more automatic encoding response (target versus non-target) was predicted to engage VLPFC in both groups. Conversely, having to overcome the prepotent encoding response (non-targets versus targets) was predicted to produce greater DLPFC activation in controls than in patients. Encoding occurred during event-related fMRI in a sample of 21 individuals with schizophrenia and 30 healthy participants. Scanning was followed by recognition testing outside the scanner.ResultsPatients were less successful differentially remembering target versus non-target stimuli, and retrieval difficulties correlated with more severe disorganized symptoms. As predicted, the target versus non-target contrast activated the VLPFC and correlated with retrieval success in both groups. Conversely, the non-target versus target contrast produced greater DLPFC activation in controls than in patients, and DLPFC activation correlated with performance only in controls.ConclusionIndividuals with schizophrenia can successfully engage the VLPFC to provide control over semantic encoding of individual items, but are specifically impaired at engaging the DLPFC to main context for task-appropriate encoding and thereby generate improved memory for target versus non-target items. This extends previous cognitive control models based on response selection tasks to the memory domain

Cognitive Control of Episodic Memory in Schizophrenia: Differential Role of Dorsolateral and Ventrolateral Prefrontal Cortex.

BackgroundDorsal (DLPFC) and ventral (VLPFC) subregions in lateral prefrontal cortex play distinct roles in episodic memory, and both are implicated in schizophrenia. We test the hypothesis that schizophrenia differentially impairs DLPFC versus VLPFC control of episodic encoding.MethodsCognitive control was manipulated by requiring participants to encode targets and avoid encoding non-targets based upon stimulus properties of test stimuli. The more automatic encoding response (target versus non-target) was predicted to engage VLPFC in both groups. Conversely, having to overcome the prepotent encoding response (non-targets versus targets) was predicted to produce greater DLPFC activation in controls than in patients. Encoding occurred during event-related fMRI in a sample of 21 individuals with schizophrenia and 30 healthy participants. Scanning was followed by recognition testing outside the scanner.ResultsPatients were less successful differentially remembering target versus non-target stimuli, and retrieval difficulties correlated with more severe disorganized symptoms. As predicted, the target versus non-target contrast activated the VLPFC and correlated with retrieval success in both groups. Conversely, the non-target versus target contrast produced greater DLPFC activation in controls than in patients, and DLPFC activation correlated with performance only in controls.ConclusionIndividuals with schizophrenia can successfully engage the VLPFC to provide control over semantic encoding of individual items, but are specifically impaired at engaging the DLPFC to main context for task-appropriate encoding and thereby generate improved memory for target versus non-target items. This extends previous cognitive control models based on response selection tasks to the memory domain